如何在谷歌云数据流中运行动态第二查询? [英] How to run dynamic second query in google cloud dataflow?

问题描述

我正在尝试进行以下操作:通过查询获取ID列表，将其转换为以逗号分隔的字符串(即"1,2,3")，然后在辅助查询中使用它.尝试运行第二个查询时，出现语法错误:

I'm attempting to do an operation wherein I get a list of Ids via a query, transform them into a string separated by commas (i.e. "1,2,3") and then use it in a secondary query. When attempting to run the second query, I'm given a syntax error:

"lambda转换的目标类型必须是接口"

"Target type of a lambda conversion must be an interface"

String query = "SELECT DISTINCT campaignId FROM `" + options.getEligibilityInputTable() + "` ";

    Pipeline p = Pipeline.create(options);
    p.apply("GetCampaignIds", BigQueryIO.readTableRows().withTemplateCompatibility().fromQuery(query).usingStandardSql())
      .apply("TransformCampaignIds",
        MapElements.into(TypeDescriptors.strings())
        .via((TableRow row) -> (String)row.get("campaignId")))
      .apply(Combine.globally(new StringToCsvCombineFn()))
      .apply("GetAllCampaigns", campaignIds -> BigQueryIO.readTableRows().withTemplateCompatibility().fromQuery("SELECT id AS campaignId, dataQuery FROM `{projectid}.mysql_standard.campaigns` WHERE campaignId IN (" + campaignIds + ")").usingStandardSql())
....

如何将查询链接在一起?

How can I chain queries together?

推荐答案

不幸的是，您无法使用现有资源执行此操作.您有两种选择:

You cannot do this with the existing sources, unfortunately. Your options here are two:

• 您从ParDo手动调用BQ API.
• 您编写了一个复杂的SQL查询来为您执行此操作.

第二个选项看起来像这样:

The second option looks something like so:

String query = "SELECT id AS campaignId, dataQuery \
               FROM `{projectid}.mysql_standard.campaigns` \
               WHERE campaignId IN ( \
                   SELECT DISTINCT campaignId \
                   FROM `" + options.getEligibilityInputTable() 
                   + "`)";

Pipeline p = Pipeline.create(options);
p.apply("GetAllCampaigns", BigQueryIO.readTableRows()
                                     .withTemplateCompatibility()
                                     .fromQuery(query)
                                     .usingStandardSql());

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